The role of life-history and ecology in the evolution of ...dro.deakin.edu.au/eserv/DU:30105842/symonds-roleoflife-2017.pdf · The role of life-history and ecology in the evolution

DRO Deakin Research Online Deakin Universityrsquos Research Repository Deakin University CRICOS Provider Code 00113B

The role of life-history and ecology in the evolution of color patterns in Australian chrysomeline beetles

Citation Tan Eunice J Reid Chris AM Symonds Matthew RE Jurado-Rivera Joseacute A and Elgar Mark A 2017 The role of life-history and ecology in the evolution of color patterns in Australian chrysomeline beetles Frontiers in ecology and evolution vol 5 Article number 140 pp 1-15 DOI httpwwwdxdoiorg103389fevo201700140

copy2017 The Authors

Reproduced by Deakin University under the terms of the Creative Commons Attribution Licence

Downloaded from DRO httphdlhandlenet10536DRODU30105842

ORIGINAL RESEARCHpublished 14 November 2017doi 103389fevo201700140

Frontiers in Ecology and Evolution | wwwfrontiersinorg 1 November 2017 | Volume 5 | Article 140

Edited by

Wayne Iwan Lee Davies

University of Western Australia

Australia

Reviewed by

Floria Mora-Kepfer Uy

University of Miami United States

Sean John Blamires

University of New South Wales

Australia

Correspondence

Mark A Elgar

melgarunimelbeduau

daggerPresent Address

Eunice J Tan

Division of Science Yale-NUS College

Singapore Singapore

Specialty section

This article was submitted to

Behavioral and Evolutionary Ecology

a section of the journal

Frontiers in Ecology and Evolution

Received 14 July 2017

Accepted 31 October 2017

Published 14 November 2017

Citation

Tan EJ Reid CAM Symonds MRE

Jurado-Rivera JA and Elgar MA (2017)

The Role of Life-History and Ecology

in the Evolution of Color Patterns in

Australian Chrysomeline Beetles

Front Ecol Evol 5140

doi 103389fevo201700140

The Role of Life-History and Ecologyin the Evolution of Color Patterns inAustralian Chrysomeline BeetlesEunice J Tan 1dagger Chris A M Reid 2 Matthew R E Symonds 3 Joseacute A Jurado-Rivera 4 and

Mark A Elgar 1

1 School of BioSciences University of Melbourne Melbourne VIC Australia 2Department of Entomology Australian

Museum Sydney NSW Australia 3 School of Life and Environmental Sciences Deakin University Burwood VIC Australia4Departament de Biologia Universitat de les Illes Balears Palma de Mallorca Spain

The variation in animal coloration patterns has evolved in response to different visual

strategies for reducing the risk of predation However the perception of animal coloration

by enemies is affected by a variety of factors including morphology and habitat We

use the diversity of Australian chrysomeline leaf beetles to explore relationships of

visual ecology to beetle morphology and color patterns There is impressive color

pattern variation within the Chrysomelinae which is likely to reflect anti-predatory

strategies Our phylogenetic comparative analyses reveal strong selection for beetles

to be less distinct from their host plants suggesting that the beetle color patterns

have a camouflage effect rather than the widely assumed aposematic function Beetles

in dark habitats were significantly larger than beetles in bright habitats potentially to

avoid detection by predators because it is harder for large animals to be cryptic in

bright habitats Polyphagous species have greater brightness contrast against their host

plants than monophagous species highlighting the conflict between a generalist foraging

strategy and the detection costs of potential predators Host plant taxamdashEucalyptus

and Acaciamdashinteracted differently with beetle shape to predict blue pattern differences

between beetle and host plant possibly an outcome of different predator complexes on

these host plants The variety of anti-predator strategies in chrysomelines may explain

their successful radiation into a variety of habitats and ultimately their speciation

Keywords color pattern anti-predator strategies phylogenetic comparative methods signaling conflicts

chrysomelines

INTRODUCTION

The pervasive risk of attack by natural enemies has favored the evolution of a variety ofanti-predator strategies (Stevens 2013) Protective color patterns are arguably among the mostwidespread of these strategies as they can reduce prey detection andor warn predators that theprey is unpalatable (Cott 1940 Ruxton et al 2004 Stevens 2007) Color patterns that resemblean animalrsquos background or mask an animalrsquos outline may reduce detection by predators (Endler1984 Cuthill et al 2005 Stevens et al 2006) On the other hand conspicuous color patterns areused to advertise the distastefulness of an organism to visually searching enemies (Roper 1990Prudic et al 2007b Skelhorn et al 2016) However these functions of color patterns may not bemutually exclusive as some color patterns may combine warning coloration at a close range with

Tan et al Color Pattern Evolution in Beetles

crypsis at a longer range (Tullberg et al 2005 Honma et al2015) As a consequence a diversity of color patterns mayderive from these different visual defense mechanisms While theadaptive significance of these color patterns are reasonably welldocumented how their evolution has been shaped by ecological(Prudic et al 2007a Mappes et al 2014) and life history factors(Ojala et al 2007 Tan et al 2016) is less clearly understood

Animal color patterns are rarely ldquomatchedrdquo with theirbackground because habitats are usually heterogeneous andtherefore provide backgrounds that vary visually in time andspace (Merilaita and Dimitrova 2014) Nevertheless backgroundmatching is especially important for individuals that are exposedwhile feeding (Pellissier et al 2011 Kjernsmo and Merilaita2012) since the risk of predation can increase by up to a 100-fold (Bernays 1997) One solution is for animals to have patcheson the body surface with a mixture of contrasting colors orluminance thatmatch different patches in the immediate adjacentsurroundings (Pellissier et al 2011 Wilts et al 2012 Espinosaand Cuthill 2014) For herbivorous animals apart from beinga food source the host plant can also affect how animals areperceived by their enemies For instance host plants can providevisual signals to deter a herbivorersquos predators (Keasar et al2013) While most species of phytophagous insects are associatedwith a small range of closely related host plant species otherspecies may have multiple associations with unrelated plants(Novotny et al 2002 2007 Jurado-Rivera et al 2009 Bakeret al 2012) Increasing the number of host plants is likely todecrease background matching and so generalist species mayface a compromise between a preferred host plant and theircapacity to be conspicuous or not

Visual signals may be constrained by morphology which isalso under selection by natural enemies Larger animals maybe under greater selection pressure because of their higherprofitability and detectability (Krebs et al 1977 Utne-Palm2000 Sandre et al 2007 Smith et al 2016) Thus the detectionof an animal can be affected by a combination of body size andcolor pattern (Karpestam et al 2014) The size of an animal canalso affect the efficacy of color patterns and thus the strengthof selection A positive correlation between warning efficacy andanimal body size suggests that warning coloration may evolvemore readily in larger animals (Gamberale and Tullberg 1998)but larger insects may not necessarily be more conspicuous(Nilsson and Forsman 2003) For instance larger-sized signalingpattern elements can accelerate the learning rate of great tits(Parus major) to unpalatable prey (Lindstroumlm et al 1999)Larger-sized prey can also induce greater avoidance behaviorin potential predators (Gamberale and Tullberg 1996b 1998Forsman and Merilaita 1999 Lindstedt et al 2008) Otherstudies reveal the advantages of gregarious aposematic prey(Gamberale and Tullberg 1996a 1998 Tan et al 2016) whichsuggest that the efficacy of the warning signal may be an effect ofthe total signaling area

In addition to size the shape of an animal affects how it isperceived An important but frequently neglected considerationis that the shape of prey will differ according to the perspectiveof the viewer For instance aerial predators such as birds orpredatory hymenoptera will take a predominantly dorsal view of

the prey while terrestrial predators such as carnivorous insectsand spiders will assess prey size from a lateral view The effectof predation on prey shape is highly variable among animal taxa(Broumlnmark and Miner 1992 Nilsson et al 1995 Outomuroand Johansson 2015) potentially affecting the mobility and thusthe ability to escape predators For instance damselflies developshort and broad hind wings in response to selection by birdpredators (Outomuro and Johansson 2015) while freshwatercarp develop deeper bodies in the presence of pike predatorswhich either render the carp less vulnerable to predation(Broumlnmark andMiner 1992) or increase handling time and thusthe opportunity to escape (Nilsson et al 1995) The distributionof color intensities on a convex shape like a beetle would varyin a natural landscape because of multiple illumination sourcessuch as light scattering from forest gaps or surrounding objects(Khang et al 2006) Studies of humans pigeons and starlingsshow that the perceived shape and depth of an object is affectedby the amount of illumination on it (Ramachandran 1988 Cooket al 2012 Qadri et al 2014) As the shape and depth of anorganism may be correlated with its nutritional return as a preyitem the shape and depth may also reflect an animalrsquos value to apredator (Stephens and Krebs 1986 Rychlik 1999)

Chrysomeline leaf beetles are a good system for investigatingthe evolution of color patterns because of their phenotypicdiversity and the variety of habitats in which they occur(Reid 2014) Australia includes 25 of the worldrsquos diversityof this subfamily sim750 species in 43 endemic genera (Reidet al 2009 Reid 2017) Leaf beetles cover a range of colorpatterns such as iridescence contrasting and mottled coloration(see Reid 2006 for details on the diversity of the colorpatterns of Australian chrysomelines) Chrysomeline beetlesare also chemically defended producing noxious secretions ofmetabolites derived from their host plants (Pasteels et al 19821983 Selman 1985a Schulz et al 1997 Termonia et al 2002) orsynthesized de novo (Blum et al 1972 Hilker and Schulz 1994)The conspicuous appearance of many chrysomelines togetherwith their defensive chemical secretions and diurnal lifestylehave led to the widespread assumption that these color patternsare aposematic and deter potential predators (Selman 1985b1994 Pasteels et al 1989 Matthews and Reid 2002)

However attributing an aposematic role to contrasting colorpatterns commonly associated with toxicity may not accuratelyreflect the adaptive significance of the beetle color patterns(Pawlik et al 1995) Chrysomelines are phytophagous withdiverse body shapes and color patterns that to varying degreesmatch or contrast with their environments that range fromrainforests to sandy deserts (Reid 2014) Most chrysomelinesare highly specialized on a single host plant genus for theirentire life cycle (Jolivet and Hawkeswood 1995 Reid 2006Jurado-Rivera et al 2009) Indeed recent analyses suggest thatchemical defenses in juvenile chrysomelines is closely linked tothe chemistry of their hosts (Rahfeld et al 2015) Despite thepresence of toxic glands in the chrysomelines the diversity ofchrysomeline color patterns suggests that these color patternsmay have evolved through mechanisms other than aposematismLeaf beetles are likely to have a large number of visual predatorsthat will view the beetles from a dorsal and a lateral view

thus exerting selection pressures on chrysomeline size andshape respectively Cursorial arachnids are potential predatorsexerting a selection pressure on chrysomelines from lateral viewwhile aerial predators such as birds and wasps are potentialpredators of beetles taking a dorsal view (Recher et al 1987Recher 1989 Recher andMajer 2006) Documented predators ofchrysomelines include wasps (Evans and Hook 1986) and birds(de Little 1979 Matthews and Reid 2002)

We investigate how beetle morphology habitat and hostplant range influence the evolution of diverse color patternswithin a single clade of chrysomeline beetles from AustraliaWe assemble a database of chrysomeline color pattern andmorphology by collecting live beetles and drawing on publishedrecords and perform phylogenetic comparative analyses to askspecific questions First are beetles visually different from theirhost plants and is this distinctiveness predicted by the host plantspecificity and light environment We predict that polyphagousspecies are visually different from their host plants because ofthe inherent differences of host plant speciesWe also predict thatbeetles that feed on similar host plant species may have broadlysimilar color patterns For instance beetles that feed on one cladeof host plants may have specific color pattern differences that arenot evident among beetles that feed on a different clade Nextwe asked if beetle morphology affects how beetles are perceivedwe predict that larger beetles may be more commonly foundin darker habitats than smaller beetles because larger beetleswhich face higher predation risks may be less conspicous inthese habitats We also predict that more convex beetles that mayappear larger to predators will be visually more distinct fromtheir host plants thereby providing a greater deterence signal

MATERIALS AND METHODS

Taxon SamplingDeceased non-iridescent chrysomeline leaf beetles tend to fade tobrown (Moore 1980 Selman 1985b Balsbaugh 1988 Lawrenceand Britton 1994 also see Figure 1) so we included live beetlesonly as a meaningful record of body color patterns Museumcollections of specimens while plentiful furnish little if anyinformation about color patterns unless the beetles possessstructural coloration

Fifty-one species of chrysomeline beetles were collected from32 locations across four states in Australia from November 2012to March 2014 (Table S1) Where possible we collected speciesrepresentative of the diversity of phenotypes in each genus Wecollected an additional 39 species of beetles during our fieldtrips but they were not represented in the molecular phylogeny(Jurado-Rivera (2014) and so were not included in this analysisOur study comprises of 143 specimens collected from a rangeof habitatsmdashrainforests dry and wet sclerophyll forests andheath Specimens have been deposited at the AustralianMuseumSydney Live beetles were photographed with their host plantin the field at a distance of sim01m during daylight hoursgenerally under clear skies We obtained digital images of thedorsal surface of each beetle as it was assumed to be the clearestexposition of its appearance to visual predators These beetlesare all dorsally convex and predators are assumed to view them

FIGURE 1 | Live and pinned specimens of chrysomelines (A) Live specimen

of an adult Paropsisterna gloriosa (B) Corresponding pinned specimen of

Paropsisterna gloriosa (Image by Sue Lindsay copy Australian Museum) (C) Live

specimen of an adult Calomela pallida (D) Corresponding pinned specimen of

Calomela pallida (Image by Sue Lindsay copy Australian Museum) The white

bars represent 5mm in each image

dorsally or laterodorsally as only the dorsal surface is exposedduring foraging mating and resting

Phylogenetic Tree InferenceWe obtained a molecular phylogeny for Australianchrysomelines previously documented in an unpublishedPhD Thesis (Jurado-Rivera 2014) Details of the molecularphylogeny construction are described in the SupplementaryMaterial (Chrysomeline molecular phylogeny Table S2) Thephylogenetic tree was visualized and modified in Mesquite 302(Maddison and Maddison 2014) The original phylogeny byJurado-Rivera (2014) was pruned to include only the species inour analysis The node ages of the tree were estimated using asemi-parametric method based on penalized likelihood (Paradiset al 2004) and the smoothing parameter used was 01 Allsubsequent analyses were performed in R Development CoreTeam (2016)

Beetle MorphologyWe investigated whether adult morphology constrains the colorpatterns of chrysomelines by obtaining measures of the lengthheight and width of each species in the sample Additionalspecimens were measured from the collection at the AustralianMuseum Sydney Where available up to 10 individuals weremeasured per species over as wide a range of collection yearsas possible The length width and height dimensions of beetlesare defined in Figure 2 and 470 beetles were measured for thispurpose (see details in Table S3) To obtain a measure of abeetlersquos elevation from its substratemdashand thus its perceived sizeby natural enemies approaching from the same substratemdashweobtained the ratio of the beetle height to the length (hereafterreferred to as convexity) Beetle height was measured as the

FIGURE 2 | Measurements of the dimensions of a beetle (A) Lateral view of

beetle depicting height measurement (B) Dorsal view of beetle depicting

length and width measurements Convexity is defined as the ratio of the beetle

height to length Images by Kindi Smith copy Australian Museum

furthest extremes of the anatomymdashie if the elytra were notenlarged and overhanging (see Figure 2A) then the maximumprojection of the metaventrite was considered the deepestpoint

Assessment of Color Pattern DifferenceRaw image files (CR2 format) with minimally processed datafrom the image sensor of the camera (Canon EOS 600D)were acquired to prevent information loss during the imagecompression process (Stevens et al 2007) Due to limitationsof the camera and lens UV coloration of the beetles and theirbackgrounds were not recorded Each photograph was takenin the presence of a card with 1 cm graduations to allow forsubsequent scaling of images All the images were then scaled inAdobe Photoshop CS6 based on the graduations present in eachimage such that the number of pixels per cm was consistent forall the images The beetle in each image was manually definedfollowing Cheney et al (2014) using a tablet and stylus Foursamples of the background were also obtained by shifting thebeetle outline to separate arbitrarily chosen positions within thebackground area of the same image

First we compared the brightness contrasts of the beetlesto their background samples by measuring the distributionof brightness contrast within each image Contrasts betweenprey and background can be important in perception andpredator avoidance learning (Gittleman and Harvey 1980 Roperand Wistow 1986 Roper and Redston 1987 Aronsson andGamberale-Stille 2009 Llandres et al 2011) The pixel intensityvariance (PIV) is a measure of the distribution of brightnesscontrast within an image In order to compare the brightnesscontrasts of the beetles to their background samples we measuredthe PIV of each beetle and background sample as

PIV =1

N minus 1

(xi minus x) (1)

where for each sample (beetle or background) N is the length ofthe data vector x is the mean of the data vector and xi is elementi of the data vector (Zylinski et al 2011) This was calculatedseparately on the red green and blue layers for each samplein MATLAB using the Image Processing Toolbox To comparethe beetle samples with their respective background samples weperformed two-tailed t-tests of the PIV of beetles against theirrespective backgrounds Where the results of the t-test indicateda significant difference between the PIV of the beetle and itsbackground the beetle was deemed different from its backgroundin terms of brightness contrast in that particular color layer(for convenience we refer to the brightness contrasts within thespecific color layers as either red green or blue contrasts)

Next we quantified and compared the color patterns of thebeetles and their backgrounds by obtaining measures of colorpattern differences This allowed comparison of the red greenand blue patterns of the beetles and their backgrounds Theunderlying assumption of this analysis is that a color patterncan be considered cryptic if it resembles a random sample of itsbackground while it must differ from its background in orderto be conspicuous (Endler 1978) This analysis does not takeinto account the vision of the viewer but it nonetheless yieldsuseful empirical information about the differences of both colorand pattern between an animal and its background and allows usto investigate the evolutionary development of color patterns inthese toxin-protected beetles The degree of resemblance betweenbeetle and visual background allows us to examine the presenceof any selection pressure because of the visual backgroundsignals

Following Zylinski et al (2011) the spatial frequency ofpatterns within each sample (beetle and background) wereanalyzed using two-dimensional Fast Fourier Transformation(FFT) This was performed separately on the red green andblue layers of each sample in MATLAB using the ImageProcessing Toolbox A log-scaled power spectrum curve wasobtained from the FFT followed by a rotational average ofthe amplitudes produced (Cheney et al 2014) The absolutedifference in area between the power spectrum curves of thebeetle and each background sample provided a quantificationof the difference in color pattern between the beetle and itsbackground This difference in color pattern between the beetleand its background was obtained separately for red blue and

green (hereafter referred to as red blue and green patterndifferences respectively) As the values for pattern differenceswere of a greater range than that described by Cheney et al(2014) we did not classify them as ldquodifferentrdquo or ldquonot differentrdquoRather we used the values of pattern differences as a continuousmeasure to compare against the ecological data These analysescannot be used to compare patterns between images because ofedge effects from the border between the beetle outline and theedge of the image (Cheney et al 2014) Although image intensityvariance and power spectrum analysis can be affected by changesin the light exposure within-image comparisons of the beetle andthe backgrounds would control for such effects

Variation in Color Differences betweenBeetle and Host PlantTo summarize the variation in color differences betweenbeetle and host plant we performed a phylogenetic PrincipleComponents Analysis using the phytools package (Revell 2012)in R This procedure takes into account the phylogenetic non-independence among species means

Ecological Data CollectionEcological data were collated for the 51 species of chrysomelinebeetles from a range of habitats Ecological data of the 51 specieswere based on conditions in the field and where necessarysupplemented by information from the literature (details inTable S3) Chrysomeline beetles are herbivores that usually onlyfeed on related host plants within a genus (Jurado-Rivera et al2009 Reid 2017) and host plant identities were used to examineif selection pressures on color patterns were specific to the hostplants

Phylogenetic Generalized Least SquaresRegressionWe used phylogenetic generalized least-squares (PGLS)regression which controls for the non-independence of speciesdata to examine the relationship of response variable (colorpattern differences) with predictor variables (beetle morphologyhost plants and light environment) For continuous variables(beetle length height convexity color pattern difference) wecalculated Pagelrsquos λ (Pagel 1997 1999) which indicates thelevel of association between the trait and phylogeny λ adopts avalue between 0 and 1 where λ = 0 indicates that closely relatedspecies do not have similar trait values and λ = 1 indicates thatclosely related species have very similar trait values

We use the caper package (Orme et al 2013) in R toperform PGLS We used a model selection approach usingAkaikersquos Information Criterion (AIC) To evaluate how muchmore likely each of our models were than the null model wecalculated the Evidence Ratio (ER) (Symonds and Moussalli2011) The alternative models were compared to the null modeland alternativemodels with less than twoAIC units better (lower)than the null model were not considered distinguishable from anull model (Symonds andMoussalli 2011) We present the ER ofthe best model compared with the null model to evaluate howthe AIC values of models were better (lower) than that of thenull model In addition to clarify how we selected our modelswe present the number of parameters (k)1i-values derived from

AICiminusAICmin Akaike weights and adjusted R2 values followingBurnham and Anderson (2002)

Effect of Light Environment on BeetleMorphologySince the distribution of light in forests can vary dependingon the vegetation structure (Ross et al 1986 Johansson 1987Constabel and Lieffers 1996 Montgomery and Chazdon 2001)we scored the light environment of each beetle specimenbased on the habitats and vegetation structure of the hostplants following the phyto-sociological classification of Groves(1999) The light environment was classified and scoredin terms of habitat (rainforest 1 wet sclerophyll 2 drysclerophyll 3 heath 4) and vegetation strata (understorey1 tree species 2) such that darker habitats and vegetationstrata have lower scores We then recorded the sum ofthese two scores for each beetle species and deemed darkerenvironments for scores le 4 (the median score acrossall species) and brighter environments for scores ge 5While this definition of light environment is arbitrary ourintention is to keep the analysis simple with a dichotomythat captures the combined effects of vegetation strata andhabitat type on the amount of light incident on the beetleand thus perception by potential predators Beetles locatedin the rainforest understorey would be in a very muchdarker environment than those found on dry sclerophyll treesImportantly these values are derived independent of our studyThus our brighterdarker habitat dichotomy is not based onan arbitrary threshold but rather reflects values that are less orgreater than the median value This binary classification of theenvironment was subsequently used in the comparative analysis(Figure 3)

Effect of Diet SpecializationAs the host plant also affects how enemies perceive their animalprey we examined whether diet specialization (monophagous orpolyphagous) affects how beetle color patterns vary with theirhost plants Using the ecological information (Table S4) wedefined beetles as monophagous if only one species of host plantwas recorded and polyphagous if more than one species of hostplant was recorded

Effect of Host Plant GeneraWe examined the effect of host plant genera on the colorpatterns and beetle morphology in more detail by selecting beetlespecies that feed on Eucalyptus (n = 13) and Acacia (n =

17) since these were the two dominant genera of host plantswithin our sample As Eucalyptus and Acacia dominate almostall of the plant associations of the Australian continent (Barlow1981) it is unsurprising that a large proportion of our sampledchrysomeline species feed on these host plants

As beetle morphology could affect the perception of the beetleagainst their host plants we then performed PGLS to test whetherbeetle length height and convexity interacted with host genera topredict color pattern differences in beetles To assess the value ofthe interaction terms we compared the models with and withoutthe interaction term using the AIC values and the calculation ofER as described above

FIGURE 3 | Molecular phylogeny of chrysomelines Corresponding beetle images (not to scale) are placed at the tips before the species names The light

environment (E) is represented by open circles (light environments) or closed circles (dark environments) Beetle length (L) is represented by the horizontal lines

adjacent to species names and the gray vertical line illustrates the average size of the chrysomelines

RESULTS

Variation in Color Differences betweenBeetle and Host PlantPhylogenetic Principle Components Analysis of the red greenand blue patterns yielded two principle components (Table 1)PC1 explained 706 of the variance (SD = 413) while PC2explained 260 of the variance (SD = 250) Green and bluepatterns are more important to PC1 while red pattern is moreimportant to PC2 Principal Component 1 (PC1) values of sistertaxa are generally similar (Figure 4A) and a similar trend is seenfor principal component 2 (PC2) values (Figure 4B)

Effect of Light Environment on BeetleMorphologyThe light environment is a good predictor of beetle length andheight Species that were found in darker environments tend to belarger than beetles in brighter environments (λ= 098 β=minus011plusmn 004 ER = 34723 Table 2 Figure 5A) Similarly species thatwere found in darker environments tend to be higher than beetlesin brighter environments (λ = 098 β = minus011 plusmn 004 ER =

979 Table 2 Figure 5B) However the light environment didnot predict beetle convexity (Table 2)

Effect of Beetle Morphology on ColorPatterns and ContrastsThe green color pattern difference between beetle and the hostplant background a measure or conspicousness increased withbeetle size (λ = 0 β = 236 plusmn 082 R2 = 015 ER = 53915Table 3) Likewise larger beetles have a greater blue patterndifference compared with their host plant (λ = 0 β = 216 plusmn

092 R2 = 010 ER = 3150 Table 3) However there was nocorrelation between beetle size and red pattern difference

The degree of brightness contrast between the beetle and itshost plant background important for predator perception ofpotential prey was not consistently predicted by the lengthheight and convexity of the beetle Beetle length did not influencethe degree of contrast between beetle and background (Table 4)For all three colors the null model was better than these modelsat predicting brightness contrasts between beetle and host plantBeetle height influences the degree of brightness contrast betweenbeetle and background in blue but not in green and red Beetleswith greater height tend to have a significant blue contrastcompared with their host plants (λ = 0 β = 082 plusmn 040 R2

= 008 ER = 2617 Table 4 Figure 6A) This was not observedfor red contrasts and green contrasts where the null model wasbetter at predicting the contrast between beetle and host plant

TABLE 1 | Loadings from phylogenetic principal component analysis of

differences in red green and blue patterns between beetles and host plants

PC1 PC2 PC3

Red pattern minus0529 0842 minus0107

Green pattern minus0932 0114 0344

Blue pattern minus0940 minus0322 minus0110

(Table 4) However the convexity of beetles influences the degreeof brightness contrast between beetle and background in blue andred colors but not in green Beetles with greater convexity tend tohave a significant blue contrast (λ = 0 β = 402 plusmn 098 R2 =

026 ER= 524times 105 Table 4 Figure 6B) and red contrast (λ =

0 β= 315plusmn 100 R2 = 017 ER= 145099 Table 4 Figure 6C)compared with their host plants This was not observed for greencontrasts (Table 4) where the null model was better at predictingthe contrast between beetle and host plant

Effect of Diet SpecializationPolyphagous beetles had greater green color pattern differencecompared with monophagous beetles (λ = 1 β = minus064 plusmn 027R2 = 010 ER = 604 Table 4) Polyphagous beetles also hadless red color pattern difference compared with monophagousbeetles (λ = 1 β = minus153 plusmn 025 R2 = 042 ER = 647 times 105Table 4) However there was no effect of diet (ie monophagousor polyphagous) on blue color pattern differences (Table 4)

Effect of Host Plant GeneraHost genera and beetle convexity predicted color patterndifferences but to a varying degree There was a significantinteraction between host generamdashAcacia and Eucalyptusmdashandbeetle convexity for blue pattern difference (λ = 1 β = 069 R2

= 032 ER = 1770 Table 5) For Acacia-feeding beetle speciesthe blue pattern difference decreased as convexity increased(Figure 7) This contrasted with Eucalyptus-feeding species asthe blue pattern difference increased with increasing convexityThe interaction between host genera and beetle convexity did notbetter predict the differences in green and red patterns comparedwith the null model (Table 5) The interaction between hostgenera and beetle length did not provide a better prediction ofcolor pattern difference compared with the null model nor didthe interaction between host genera and beetle height provide abetter prediction of color pattern difference compared with thenull model (Table 5)

DISCUSSION

Our results reveal considerable variation in the color patterndifferencemdashquantitative measures of the difference of both colorand patternmdashbetween Australian chrysomeline beetles and theirhost plants and that this variation is predicted by the host plantspecificity of the beetles and their light environment We foundthat beetle morphology effects how beetles may be perceived intwo ways (i) larger beetles have a greater green and blue patterndifference compared with their host plants and (ii) beetles withgreater convexity tend to have a significant difference in redand blue contrasts compared with their host plants Diet andhost plant choices also influence beetle color pattern differencesPolyphagous species had significantly greater green differencecompared with monophagous beetles but significantly less reddifference compared with monophagous beetles Finally hostplant taxa influence beetle color patterns with blue color patterndifferences significantly lower for Acacia-feeding species butsignificantly greater for the more convex Eucalyptus-feedingspecies

FIGURE 4 | Species values of principal components from the phylogenetic principal components analysis of differences in red green and blue patterns between

beetles and host plants mapped onto the phylogeny of the chrysomelines Color on the heat map represent PC1 (A) and PC2 (B) values of species (see legend for

scale) but do not represent the actual color of the beetles

TABLE 2 | Effect of light environment on beetle morphology

Candidate models k Adjusted R2 AIC value 1i wi

Height 3 010 minus7263 0 1

Null model ndash 0 minus6807 456 0

Length 3 013 minus8151 0 1

Convexity 3 minus002 minus16285 199 0

FIGURE 5 | Boxplots illustrating the effect of light environment on beetle

morphology The x-axes represent the light environments as dark or bright

Beetles with greater length (A) and height (B) tend to be in dark environments

instead of bright environments

Cott (1940) predicted that larger animals should evolveconspicuous coloration because it is harder for large animalsto be cryptic Our findings are broadly consistent withthis predictionmdashlarger beetles were more different from thebackground in blue and green but not red Red color is aform of aposematic coloration for a range of other organismsincluding lepidopterans coleopterans and hemipterans (Jones1932 Lindstedt et al 2011 Wee and Monteiro 2017)However the difference in red pattern does not differ withchrysomeline beetle length as might be expected if red wasthe major component of conspicuous coloration Indeed astudy of a European chrysomeline indicates that the blue-green metallic color of the beetles are a form of warningcoloration (Borer et al 2010) There are several explanationsfor the variation in the colors that may be involved in warningcoloration in these beetles First chrysomeline beetles do notvary much in red second physiological constraints may limitthe beetles from exhibiting red patterns third differencesin red may generate consequences that have a counteractiveeffect such as attracting potential predators The beetles inour study ranged from individuals that were entirely red(Oomela variabilis) to beetles that possessed little or no red(Peltoschema orphana) Physiological constraints are unlikelyto limit red patterns of beetles through the sequestration orproduction of red patterns since species across the phylogenymdashPeltoschema oceanica Paropsisterna nobilitata and Oomeladistinctamdashpossess red patterns as do other chrysomelid species(for instance see Kurachi et al 2002 Keasar et al 2013

TABLE 3 | Effect of beetle morphology and diet specialization on color pattern

differences

Blue Height 3 008 14204 020 0332

Length 3 008 14184 0 0366

Convexity 3 001 14701 517 0028

Diet specialization 3 minus002 14719 535 0025

Height + length 5 005 14363 179 0132

Height length 5 007 14541 357 0045

Null model ndash 0 14529 345 0071

Green Height 3 009 13202 224 0177

Length 3 013 12978 0 0543

Convexity 3 minus002 13806 828 0009

Height + length 5 011 13172 194 0181

Height length 5 009 13372 394 0056

Red Height 3 minus001 13002 164 0133

Length 3 000 12939 101 0184

Height + length 5 minus001 13094 256 0074

Height length 5 minus002 13220 382 0033

Martiacutenez and Plata-Rueda 2014) The third explanation is morelikely where differences in red pattern between the beetlesand their background may attract potential predators Thusinstead of increasing inconspicuousness through red patternsan alternative anti-predator strategy for larger animals is tofavor darker environments which is what we found speciesin darker environments tend to be larger while beetles inlighter environments tending to be smaller Whether selectionon increased body length caused a move to darker environmentsor whether a move to darker environments relaxed selection ongreater body length and the color patterns remains unknown

There is a potential conflict between dietary preferencesand avoiding detection by predators For example species witha generalist diet may encounter a range of backgrounds andthus be at times conspicuous or inconspicuous Indeed Arenasand Stevens (2017) found that aposematic ladybird speciesthat were specialists had evolved the optimal signal of beingmore contrasting against the background that they were mostcommonly on For leaf beetles in our study polyphagous specieshad significantly greater green pattern differences to their hostplants compared with monophagous species However lightreflected from leaves and soil is dominated by green and yellow(Menzel 1979 Chittka et al 1994) and the ubiquity of greenin the environment may explain the persistence of greater greenpattern differences between polyphagous beetles and their hostplants Interestingly polyphagous beetles had significantly lessred difference compared with monophagous beetles Togetherwith our findings that red pattern does not differ with beetlelength this suggests that the less common adoption of a typicalconspicuous color red by polyphagous species could be to

TABLE 4 | Effect of beetle morphology on brightness contrasts

Blue Height 3 006 7044 1101 0003

Length 3 minus002 7435 1492 0000

Convexity 3 024 5943 0 0722

Diet specialization 3 001 7296 1353 0001

Height + length 5 021 6239 296 0144

Height length 5 023 6226 283 0128

Green Height 3 000 7669 084 0172

Length 3 000 7697 112 0150

Height length 5 004 7684 099 0117

Red Height 3 006 6838 564 0041

Length 3 minus001 7141 867 0009

Convexity 3 015 6274 0 0692

Height + length 5 012 6570 296 0138

Height length 5 012 6613 339 0093

limit conspicuousness when they feed on diverse backgroundsRecent studies of lizards (Marshall et al 2016) and crabs (Uyet al 2017) indicate that animals actively choose to match theirbackground As the spectral sensitivities of chrysomelids appearto be limited to UV blue and green but not red (Sharkey et al2017) active background matching may not fully explain colorpattern differences of beetles with their host plant

Most studies that investigate the antipredator function of colorpatterns in insects focus predominantly on avian predators (egGreenwood et al 1981 Roper and Cook 1989 Roper 1990Gamberale and Tullberg 1996a Marples et al 1998 Gamberale-Stille and Tullberg 1999 Lindstroumlm et al 2001 Thomas et al2003 Forsman and Herrstroumlm 2004 Exnerovaacute et al 2006Rowland et al 2007 Sandre et al 2010 Ihalainen and Lindstedt2012) Yet insect prey species such as chrysomeline beetlesmay also be subject to predation by much smaller animalsincluding spiders and predatory insects Different predators willview the beetles from different perspectives and this is likely tohave an impact on the selection pressures favoring anti-predatorresponses For example avian predators will view the beetlesfrom above and identify the length of the animal from the dorsalperspective while smaller invertebrates such as predatory insectsand spiders may be approaching from the same substrate and willtake a dorsal perspective

We found no evidence that beetle length and host generapredicted color patterns On the other hand the convexity ofthe beetles and host genera appear to be more important inpredicting color pattern differences In addition our studiesindicate that beetles with greater convexity tend to have asignificant red and blue contrast compared with their hostplants but this was not observed for green contrasts Thus it

is surprising to see a lack of interaction between color patternand contrasts with beetle length The influence of body convexityon conspicuousness is not widely recognized but our resultsreveal there was a significant interaction between the convexity ofbeetles and host genera for blue pattern differences As convexityincreased the blue pattern difference decreased for Acacia-feeding species but increased for Eucalyptus-feeding speciesThis trend is expected for both beetle length and convexity ifthere are consistent differences in both the color and nutritionalvalue of the leaves of Acacia compared with Eucalyptus speciesHowever a pattern emerges for convexity only suggesting thatthe selection pressure comes from predators that view the beetleslaterally The dissimilar trends observed in blue pattern differencebetween Acacia and Eucalyptus feeding species suggest that thebeetles are subjected to different predation pressures on thesehost genera likely because of different guilds of predators on theAcacia and Eucalyptus host genera

Leaf beetles are likely to have a large number of visualpredators that will view the beetles from a lateral perspectiveSuch predators would have to be on the same substrate as thebeetles Active hunting arachnids are potential predators exertinga selection pressure on chrysomelines as arachnids would viewthe beetles at a lateral perspective without succumbing totheir chemical defenses (Hilbeck and Kennedy 1996 Nahrunget al 2008 Lundgren et al 2009) Most arachnid species aresensitive to green while a few taxa are sensitive to blue andred wavelengths (Dahl and Granda 1989 Peaslee and Wilson1989 Zurek et al 2015) Combined the visual system ofpotential arachnid predators and fewer arachnids on Eucalypts(Woinarski and Cullen 1984) may result in low selectionpressure from arachnid predators explaining why beetles feedingon Eucalyptus can evolve different blue patterns from theirbackground

In contrast selection pressures on beetle length are likelyto be influenced by predators taking a dorsal perspective suchas insectivorous birds Birds are important predators of beetlesin Eucalypt forests (Recher and Majer 2006) and potentialpredators of chrysomeline beetles are thornbills (Acanthiza)that forage on arthropods on Eucalypt foliage (Recher et al1987 Recher 1989) Insectivorous birds can be highly selectivebetween different species of Eucalypts and Acacia (Recher1989 Recher et al 1996 Dean et al 2002) which may reflectarthropod abundance on Eucalyptus species (Recher and Majer1994) Indeed avian species richness is correlated with vegetationstructure complexity and species (Shurcliff 1980 Nally et al2008 Brady and Noske 2010) and with rainfall (Tischler et al2013) and the greater the ratio of Eucalypts to Acacia the higherthe avian species richness (Brady and Noske 2010) Howeveras avian species and individuals may differ in their reactions toaposematic prey (Exnerovaacute et al 2008 Svaacutedovaacute et al 2010)there may be varying selection pressures on leaf beetle colorpattern Together the background and the predator communitycan affect the direction and strength of selection for warningcoloration (Prudic et al 2007a Lindstedt et al 2011) Manyavian species are sensitive to red in addition to green and blue(see review by Jones et al 2007) and leaf beetles may haveevolved weak aposematic signaling because of the variety of avian

FIGURE 6 | Boxplots illustrating the effect of beetle height on the brightness contrast between beetle and host plant The x-axis represents the absence or presence

of contrast between the beetle and its background (A) Beetles with greater height tend to have a significant difference in blue contrast with the host plant Beetles

with greater convexity tend to have a significant difference in (B) blue and (C) red contrasts with the host plant

TABLE 5 | Effect of host plant and beetle morphology on color pattern differences

Blue Host plant 3 004 8337 669 0048

Height 3 004 8341 673 0047

Length 3 006 8265 597 0068

Host plant height 5 002 8573 905 0008

Host plant length 5 000 8620 952 0006

Host plant convexity 5 027 7668 0 0757

Green Host plant 3 005 6796 0 0290

Height 3 minus003 7012 216 0099

Length 3 minus003 7018 222 0095

Red Host plant 3 minus001 7745 121 0177

Height 3 minus003 7818 194 0122

Length 3 minus003 7818 194 0123

Host plant height 5 minus002 7949 325 0036

Host plant length 5 minus003 7995 371 0028

Host plant convexity 5 minus006 8068 444 0020

predators and the varying tendency of avian predators to attackdefended prey (Endler and Mappes 2004)

Comparative studies like this can be a tool to identifybroad trends of selection that can inform future experimentalstudies (Harvey and Pagel 1991) Chrysomelines possess adiverse defensive chemistry including compounds from variouschemical classes such as phenolic cyanogenic and cardiacglycosides pyrrolizidine alkaloids and cucurbitacins (reviewedby Opitz and Muumlller 2009 Morgan 2010) As de novo

FIGURE 7 | Blue pattern differences between Acacia and Eucalyptus feeding

species Closed circles represent the raw data of Acacia-feeding species while

open circles represent the raw data points of Eucalyptus-feeding species The

dark gray line represents the phylogenetically-corrected regression for

Acacia-feeding species while the light gray line represents the

phylogenetically-corrected regression for Eucalyptus-feeding species

synthesis of defensive compounds is expected to be energeticallymore costly (Kirsch et al 2011) species that use host-derived defensive compounds could potentially invest moreon costly color patterns A significant correlation in theevolution of toxicity and conspicuous coloration is found inthe dendrobatid frogs (Summers and Clough 2001) and asimilar process may influence the evolution of coloration inthe Australian chrysomelines A good system to investigatethe effect of defensive compounds on color patterns wouldbe the chrysomelines of the genus Phratora (Koumlpf et al1998) The color patterns of species within this genus whichhave been extensively studied in Europe because of theireconomic significance have not been quantified but there

is considerable variation in their chemical defenses and hostplants

The common wisdom is that bright coloration such asthat found in leaf beetles reflects defense through aposematiccoloration but this singular explanation is not supported byour data The variation in color patterns of chrysomelines isinfluenced and possibly limited bymorphological and ecologicalfactors including beetle length light environment and hostplant use Importantly this indicates that when closely relatedchemically defended species radiate into similar ecologicalhabitats and hosts their color patterns change as a resultof novel selection pressures For example diet specializationaffected the color difference between beetle and background withpolyphagous species having significantly greater green differencebut less red difference compared with monophagous beetles Thejoint evolution of color pattern and habitat choice could leadto species divergence with selection through natural enemiesdriving different sized species into different habitats of darkerand lighter environments Our study reveals the complexitiesinvolved in the evolution of color patterns in a single relativelyisolated clade of Australian chrysomelines which could reflectselection pressures exerted by diverse predators

ETHICS STATEMENT

The research reported in this paper which involved insects onlywas exempt from ethical approval procedures

AUTHOR CONTRIBUTIONS

ET CR MS and ME conceived and designed the work ET andCR collected the live specimens JJ-R collected and analyzed thedata for the molecular phylogeny ET MS and ME analyzedand interpreted the comparative data ET and ME drafted thework ET CR MS JJ-R and ME revised the work critically forimportant intellectual content

FUNDING

The authors thank the Holsworth Wildlife Endowment forfunding the research and the Australian Postgraduate Award andthe International Postgraduate Research Scholarship for fundingETrsquos postgraduate candidacy

ACKNOWLEDGMENTS

The authors thank Nik Tatarnic Kate Umbers Antoni LunnDaisy Lunn Daniel Dobrosak Evi Reid and Ewan Reid for adviceand help with beetle collections

SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be foundonline at httpswwwfrontiersinorgarticles103389fevo201700140fullsupplementary-material

REFERENCES

Arenas L M and Stevens M (2017) Diversity in warning colorationis easily recognized by avian predators J Evol Biol 30 1288ndash1302doi 101111jeb13074

Aronsson M and Gamberale-Stille G (2009) Importance of internal patterncontrast and contrast against the background in aposematic signals Behav Ecol20 1356ndash1362 doi 101093behecoarp141

Baker M R Kitching R L Reid C A M and Sheldon F (2012)Coleoptera (Chrysomelidae Coccinellidae Curculionoidea) in sclerophyllwoodland variation in assemblages among host plants and host specificityof phytophagous and predatory beetles Aust J Entomol 51 145ndash153doi 101111j1440-6055201100851x

Balsbaugh E U Jr (1988) ldquoMimicry and the chrysomelidaerdquo in Biology of

Chrysomelidae eds P Jolivet E Petitpierre and T H Hsiao (DordrechtKluwer Academic Publishers) 261ndash284

Barlow B A (1981) ldquoThe Australian flora its origin and evolutionrdquo in The Flora

of Australia eds R Robertson B G Briggs H Eichler L Pedley J H RossD F Symon P G Wilson A McCusker and A S George (Canberra ACTAustralian Government Publishing Service) 25ndash75

Bernays E A (1997) Feeding by lepidopteran larvae is dangerous Ecol Entomol

22 121ndash123 doi 101046j1365-2311199700042xBlum M S Brand J M Wallace J B and Fales H M (1972) Chemical

characterization of the defensive secretion of a chrysomelid larva Life Sci

11(10 Pt 2) 525ndash531 doi 1010160024-3205(72)90286-XBorer M Van Noort T Rahier M and Naisbit R E (2010) Positive frequency-

dependent selection on warning color in alpine leaf beetles Evolution 643629ndash3633 doi 101111j1558-5646201001137x

Brady C J and Noske R A (2010) Succession in bird and plantcommunities over a 24-year chronosequence of mine rehabilitationin the australian monsoon tropics Restor Ecol 18 855ndash864doi 101111j1526-100X200800511x

Broumlnmark C and Miner J G (1992) Predator-induced phenotypicalchange in body morphology in Crucian carp Science 258 1348ndash1350doi 101126science25850861348

Burnham K P and Anderson D R (2002) Model Selection and Multimodel

Inference A Practical Information-Theoretic Approach New York NYSpringer-Verlag

Cheney K L Cortesi F How M J Wilson N G Blomberg S P Winters AE et al (2014) Conspicuous visual signals do not coevolve with increased bodysize in marine sea slugs J Evol Biol 27 676ndash687 doi 101111jeb12348

Chittka L Shmida A Troje N and Menzel R (1994) Ultraviolet as acomponent of flower reflections and the colour perception of HymenopteraVis Res 34 1489ndash1508 doi 1010160042-6989(94)90151-1

Constabel A J and Lieffers V J (1996) Seasonal patterns of light transmissionthrough boreal mixedwood canopies Can J For Res 26 1008ndash1014doi 101139x26-111

Cook R G Qadri M A J Kieres A and Commons-Miller N(2012) Shape from shading in pigeons Cognition 124 284ndash303doi 101016jcognition201205007

Cott H B (1940) Adaptive Coloration in Animals London MethuenCuthill I C Stevens M Sheppard J Maddocks T Parraga C A and

Troscianko T S (2005) Disruptive coloration and background patternmatching Nature 434 72ndash74 doi 101038nature03312

Dahl R D and Granda A M (1989) Spectral sensitivities of photoreceptors inthe ocelli of the tarantula Aphonopelma chalcodes (Araneae Theraphosidae) JArachnol 17 195ndash205

Dean W R J Anderson M D Milton S J and Anderson T A (2002) Avianassemblages in native Acacia and alien Prosopis drainage line woodland in theKalahari South Africa J Arid Environ 51 1ndash19 doi 101006jare20010910

de Little D W (1979) Taxonomic and Ecological Studies of the Tasmanian

Eucalypt-Defoliating Paropsids PhD University of TasmaniaEndler J A (1978) A predatorrsquos view of animal color patterns Evol Biol 11

319ndash364 doi 101007978-1-4615-6956-5_5

Endler J A (1984) Progressive background matching in moths anda quantitative measure of crypsis Biol J Linn Soc 22 187ndash231doi 101111j1095-83121984tb01677x

Endler J A and Mappes J (2004) Predator mixes and the conspicuousness ofaposematic signals Am Nat 163 532ndash547 doi 101086382662

Espinosa I and Cuthill I C (2014) Disruptive colouration and perceptualgrouping PLoS ONE 9e87153 doi 101371journalpone0087153

Evans H E and Hook A W (1986) Prey selection by Australian wasps ofthe genus Cerceris (Hymenoptera Sphecidae) J Nat Hist 20 1297ndash1307doi 10108000222938600770861

Exnerovaacute A Svaacutedovaacute K Fousovaacute P Fuciacutekovaacute P JeŽovaacute D NiederlovaacuteA et al (2008) European birds and aposematic Heteroptera review ofcomparative experiments Bull Insectol 61 163ndash165

Exnerovaacute A Svadovaacute K Štys P Barcalovaacute S Landovaacute EProkopovaacute M et al (2006) Importance of colour in the reactionof passerine predators to aposematic prey experiments with mutantsof Pyrrhocoris apterus (Heteroptera) Biol J Linn Soc 88 143ndash153doi 101111j1095-8312200600611x

Forsman A andHerrstroumlm J (2004) Asymmetry in size shape and color impairsthe protective value of conspicuous color patterns Behav Ecol 15 141ndash147doi 101093behecoarg092

Forsman A and Merilaita S (1999) Fearful symmetry pattern size andasymmetry affects aposematic signal efficacy Evol Ecol 13 131ndash140doi 101023A1006630911975

Gamberale G and Tullberg B S (1996a) Evidence for a more effectivesignal in aggregated aposematic prey Anim Behav 52 597ndash601doi 101006anbe19960200

Gamberale G and Tullberg B S (1996b) Evidence for a peak-shift inpredator generalization among aposematic prey Proc Biol Sci 263 1329ndash1334doi 101098rspb19960195

Gamberale G and Tullberg B S (1998) Aposematism and gregariousness thecombined effect of group size and coloration on signal repellence Proc BiolSci 265 889ndash894 doi 101098rspb19980374

Gamberale-Stille G and Tullberg B (1999) Experienced chicks show biasedavoidance of stronger signals an experiment with natural colour variationin live aposematic prey Evol Ecol 13 579ndash589 doi 101023A1006741626575

Gittleman J L and Harvey P H (1980) Why are distasteful prey not crypticNature 286 149ndash150 doi 101038286149a0

Greenwood JWood E and Batchelor S (1981) Apostatic selection of distastefulprey Heredity 47 27ndash34 doi 101038hdy198156

Groves R H (1999) ldquoPresent vegetation typesrdquo in Flora of Australia (MelbourneVIC Australian Biological Resources StudyCSIRO Publishing)

Harvey P H and Pagel M (1991) The Comparative Method in Evolutionary

Biology Oxford Oxford University PressHilbeck A and Kennedy G G (1996) Predators feeding on the colorado

potato beetle in insecticide-free plots and insecticide-treated commercialpotato fields in Eastern North Carolina Biol Control 6 273ndash282doi 101006bcon19960034

Hilker M and Schulz S (1994) Composition of larval secretion of Chrysomela

lapponica (Coleoptera Chrysomelidae) and its dependence on host plant JChem Ecol 20 1075ndash1093 doi 101007BF02059744

Honma A Mappes J and Valkonen J K (2015) Warning coloration can bedisruptive aposematic marginal wing patterning in the wood tiger moth EcolEvol 5 4863ndash4874 doi 101002ece31736

Ihalainen E and Lindstedt C (2012) Do avian predators select forseasonal polyphenism in the European map butterfly Araschnia

levana (Lepidoptera Nymphalidae) Biol J Linn Soc 106 737ndash748doi 101111j1095-8312201201922x

Johansson T (1987) Irradiance in thinnedNorway spruce (Picea abies) stands andthe possibilities to prevent suckers of broadleaved trees For Ecol Manage 20307ndash319 doi 1010160378-1127(87)90087-9

Jolivet P H and Hawkeswood T J (1995) Host-Plants of Chrysomelidae of the

World An Essay about the Relationships between the Leaf-Beetles and their

Food-Plants Leiden BackhuysJones F M (1932) Insect coloration and the relative acceptability

of insects to birds Trans R Entomol Soc Lond 80 345ndash371doi 101111j1365-23111932tb03313x

Jones M P Pierce K E Jr and Ward D (2007) Avian vision a review of formand function with special consideration to birds of prey J Exot Pet Med 1669ndash87 doi 101053jjepm200703012

Jurado-Rivera J A (2014) Filogenia Molecular Sistemaacutetica y Evolucioacuten de

los Chrysomelinae Australianos (Coleoptera Chrysomelidae) PhD thesisUniversity of the Balearic Islands Spain

Jurado-Rivera J A Vogler A P Reid C A M Petitpierre E and Gomez-Zurita J (2009) DNA barcoding insect-host plant associations Proc Biol Sci276 639ndash648 doi 101098rspb20081264

Karpestam E Merilaita S and Forsman A (2014) Body size influencesdifferently the detectabilities of colour morphs of cryptic prey Biol J Linn Soc113 112ndash122 doi 101111bij12291

Keasar T Kishinevsky M Shmida A Gerchman Y Chinkov NKoplovich A et al (2013) Plant-derived visual signals may protect beetleherbivores from bird predators Behav Ecol Sociobiol 67 1613ndash1622doi 101007s00265-013-1572-z

Khang B G Koenderink J J and Kappers A M L (2006) Perception ofillumination direction in images of 3-D convex objects influence of surfacematerials and light fields Perception 35 625ndash645 doi 101068p5485

Kirsch R Vogel H Muck A Reichwald K Pasteels J M andBoland W (2011) Host plant shifts affect a major defense enzymein Chrysomela lapponica Proc Natl Acad Sci USA 108 4897ndash4901doi 101073pnas1013846108

Kjernsmo K and Merilaita S (2012) Background choice as an anti-predatorstrategy the roles of background matching and visual complexity inthe habitat choice of the least killifish Proc Biol Sci 279 4192ndash4198doi 101098rspb20121547

Koumlpf A Rank N E Roininen H Julkunen-Tiitto R Pasteels J M andTahvanainen J (1998) The evolution of host-plant use and sequestration in theleaf beetle genus Phratora (Coleoptera Chrysomelidae) Evolution 52 517ndash528doi 101111j1558-56461998tb01651x

Krebs J R Erichsen J T Webber M I and Charnov E L (1977) Optimalprey selection in the great tit (Parus major) Anim Behav 25 (Pt 1) 30ndash38doi 1010160003-3472(77)90064-1

Kurachi M Takaku Y Komiya Y and Hariyama T (2002) The originof extensive colour polymorphism in Plateumaris sericea (Chrysomelidae

Coleoptera) Naturwissenschaften 89 295ndash298 doi 101007s00114-002-0332-0Lawrence J F and Britton E B (1994) Australian Beetles Melbourne VIC

Melbourne University PressLindstedt C Eager H Ihalainen E Kahilainen A Stevens M and

Mappes J (2011) Direction and strength of selection by predators forthe color of the aposematic wood tiger moth Behav Ecol 22 580ndash587doi 101093behecoarr017

Lindstedt C Lindstroumlm L and Mappes J (2008) Hairiness and warning coloursas components of antipredator defence additive or interactive benefits Anim

Behav 75 1703ndash1713 doi 101016janbehav200710024Lindstroumlm L Alatalo R V Lyytinen A and Mappes J (2001) Predator

experience on cryptic prey affects the survival of conspicuous aposematic preyProc Biol Sci 268 357ndash361 doi 101098rspb20001377

Lindstroumlm L Alatalo R V Mappes J Riipi M and Vertainen L (1999)Can aposematic signals evolve by gradual change Nature 397 249ndash251doi 10103816692

Llandres A L Gawryszewski F M Heiling A M and Herberstein ME (2011) The effect of colour variation in predators on the behaviour ofpollinators australian crab spiders and native bees Ecol Entomol 36 72ndash81doi 101111j1365-2311201001246x

Lundgren J G Ellsbury M E and Prischmann D A (2009) Analysis of thepredator community of a subterranean herbivorous insect based on polymerasechain reaction Ecol Appl 19 2157ndash2166 doi 10189008-18821

Maddison W P and Maddison D R (2014) Mesquite A Modular System for

Evolutionary Analysis Version 30 Available online at httpmesquiteprojectorg

Mappes J Kokko H Ojala K and Lindstroumlm L (2014) Seasonal changes inpredator community switch the direction of selection for prey defences NatCommun 5 5016 doi 101038ncomms6016

Marples N Roper T J and Harper D G C (1998) Responses of wildbirds to novel prey evidence of dietary conservatism Oikos 83 161ndash165doi 1023073546557

Marshall K L A Philpot K E and Stevens M (2016) Microhabitat choice inisland lizards enhances camouflage against avian predators Sci Rep 619815doi 101038srep19815

Martiacutenez L C and Plata-Rueda A (2014) Biological aspects and foodconsumption of oil palm fruit scraper Demotispa neivai (ColeopteraChrysomelidae) J Oil Palm Res 26 47ndash53

Matthews E G and Reid C A M (2002)A guide to the Genera of Beetles of South

Australia Part 8 Adelaide South Australian MuseumMenzel R (1979) ldquoSpectral sensitivity and color vision in invertebratesrdquo in

Comparative Physiology and Evolution of Vision in Invertebrates A Invertebrate

Photoreceptors eds H Autrum M F Bennett B Diehn K Hamdorf MHeisenberg M Jaumlrvilehto P Kunze R Menzel W H Miller A W Snyder DG Stavenga M Yoshida and H Autrum (Berlin Heidelberg Springer BerlinHeidelberg) 503ndash580

Merilaita S and Dimitrova M (2014) Accuracy of background matchingand prey detection predation by blue tits indicates intense selectionfor highly matching prey colour pattern Funct Ecol 28 1208ndash1215doi 1011111365-243512248

Montgomery R A and Chazdon R L (2001) Forest structure canopyarchitecture and light transmittance in tropical wet forests Ecology 822707ndash2718 doi 1018900012-9658(2001)082[2707FSCAAL]20CO2

Moore B P (1980) A Guide to the Beetles of South-Eastern Australia GreenwichAustralian Entomological Press

Morgan D E (2010) ldquoPlant substances altered and sequestered by insectsrdquo inBiosynthesis in Insects (Cambridge Royal Society of Chemistry) 315ndash331

Nahrung H F Duffy M P Lawson S A and Clarke A R (2008) Naturalenemies of Paropsis atomaria Olivier (Coleoptera Chrysomelidae) in south-eastern Queensland eucalypt plantations Aust J Entomol 47 188ndash194doi 101111j1440-6055200800656x

Nally R M Fleishman E Thomson J R and Dobkin D S (2008) Use of guildsfor modelling avian responses to vegetation in the Intermountain West (USA)Glob Ecol Biogeogr 17 758ndash769 doi 101111j1466-8238200800409x

Nilsson M and Forsman A (2003) Evolution of conspicuous colouration bodysize and gregariousness a comparative analysis of lepidopteran larvae EvolEcol 17 51ndash66 doi 101023A1022417601010

Nilsson P A Broumlnmark C and Pettersson L B (1995) Benefits of apredator-Induced morphology in crucian carp Oecologia 104 291ndash296doi 101007BF00328363

Novotny V Basset Y Miller S E Drozd P and Cizek L (2002) Hostspecialization of leaf-chewing insects in a New Guinea rainforest J Anim Ecol

71 400ndash412 doi 101046j1365-2656200200608xNovotny V Miller S E Hulcr J Drew R A I Basset Y Janda M et al

(2007) Low beta diversity of herbivorous insects in tropical forestsNature 448692ndash695 doi 101038nature06021

Ojala K Lindstroumlm L and Mappes J (2007) Life-history constraints andwarning signal expression in an arctiid moth Funct Ecol 21 1162ndash1167doi 101111j1365-2435200701322x

Opitz S W and Muumlller C (2009) Plant chemistry and insect sequestrationChemoecology 19 117ndash154 doi 101007s00049-009-0018-6

Orme D Freckleton R Thomas G Petzoldt T Fritz S Isaac N et al (2013)caper Comparative Analyses of Phylogenetics and Evolution in R R packageversion 052 Available online at httpsCRANR-projectorgpackage=caper

Outomuro D and Johansson F (2015) Bird predation selects for wing shapeand coloration in a damselfly J Evol Biol 28 791ndash799 doi 101111jeb12605

Pagel M (1997) Inferring evolutionary processes from phylogenies Zool Scr 26331ndash348 doi 101111j1463-64091997tb00423x

Pagel M (1999) Inferring the historical patterns of biological evolution Nature401 877ndash884 doi 10103844766

Paradis E Claude J and Strimmer K (2004) APE analyses ofphylogenetics and evolution in R language Bioinformatics 20 289ndash290doi 101093bioinformaticsbtg412

Pasteels J M Braekman J C Daloze D and Ottinger R (1982) Chemicaldefence in chrysomelid larvae and adults Tetrahedron 38 1891ndash1897doi 1010160040-4020(82)80038-0

Pasteels J M Rowell-Rahier M Brackman J C Daloze D and Duffey S(1989) Evolution of exocrine chemical defense in leaf beetles (ColeopteraChrysomelidae) Experientia 45 295ndash300 doi 101007BF01951815

Pasteels J M Rowell-Rahier M Braekman J C and Dupont A(1983) Salicin from host plant as precursor of salicylaldehyde indefensive secretion of Chrysomeline larvae Physiol Entomol 8 307ndash314doi 101111j1365-30321983tb00362x

Pawlik J Chanas B Toonen R and Fenical W (1995) Defenses of Caribbeansponges against predatory reef fish I Chemical deterrency Mar Ecol Prog Ser

127 183ndash194 doi 103354meps127183Peaslee A G and Wilson G (1989) Spectral sensitivity in jumping

spiders (Araneae Salticidae) J Comp Physiol A 164 359ndash363doi 101007BF00612995

Pellissier L Wassef J Bilat J Brazzola G Buri P Colliard C et al(2011) Adaptive colour polymorphism of Acrida ungarica H (OrthopteraAcrididae) in a spatially heterogeneous environment Acta Oecologica 3793ndash98 doi 101016jactao201012003

Prudic K L Oliver J C and Sperling F A H (2007a) The signal environmentis more important than diet or chemical specialization in the evolutionof warning coloration Proc Natl Acad Sci USA 104 19381ndash19386doi 101073pnas0705478104

Prudic K L Skemp A K and Papaj D R (2007b) Aposematic colorationluminance contrast and the benefits of conspicuousness Behav Ecol 18 41ndash46doi 101093behecoarl046

Qadri M A J Romero M L and Cook R G (2014) Shape fromshading in starlings (Sturnus vulgaris) J Comp Psychol 127 343ndash356doi 101037a0036848

R Core Team (2016) R A Language and Environment for Statistical Computing

Vienna R Foundation for Statistical Computing Available online at httpwwwR-projectorg

Rahfeld P Haeger W Kirsch R Pauls G Becker T Schulze E et al (2015)Glandular β-glucosidases in juvenile Chrysomelina leaf beetles support theevolution of a host-plant-dependent chemical defense Insect Biochem Mol

Biol 58 28ndash38 doi 101016jibmb201501003Ramachandran V S (1988) Perception of shape from shading Nature 331

163ndash166 doi 101038331163a0Recher H F (1989) Foraging segregation of australian warblers (Acanthizidae)

in open forest near Sydney New South Wales Emu 89 204ndash215doi 101071MU9890204

Recher H F DavisW E andHolmes R T (1987) Ecology of brown and striatedthornbills in forests of South-eastern New South Wales with comments onforest management Emu 87 1ndash13 doi 101071MU9870001

Recher H F and Majer J D (1994) On the selection of tree species byAcanthizidae in open-forest near Sydney New South Wales Emu 94 239ndash245doi 101071MU9940239

Recher H F and Majer J D (2006) Effects of bird predation on canopyarthropods in wandoo Eucalyptus wandoowoodlandAustral Ecol 31 349ndash360doi 101111j1442-9993200601555x

Recher H F Majer J D and Ganesh S (1996) Eucalypts arthropods and birdson the relation between foliar nutrients and species richness For Ecol Manage

85 177ndash195 doi 101016S0378-1127(96)03758-9Reid C A M (2006) A taxonomic revision of the Australian Chrysomelinae

with a key to the genera (Coleoptera Chrysomelidae) Zootaxa 1292 1ndash119doi 1011646zootaxa129211

Reid C A M (2014) ldquoChrysomelinae Latreille 1802rdquo in Coleoptera Beetles

Morphology and Systematics (Phytophaga) Vol 3 eds R A B Leschen and RG Beutel (Berlin De Gruyter) 243ndash251

Reid C A M (2017) Australopapuan leaf beetle diversity the contributionsof hosts plants and geography Austral Entomol 56 123ndash137doi 101111aen12251

Reid C A M Jurado-Rivera J A and Beatson M (2009) A new genusof Chrysomelinae from Australia (Coleoptera Chrysomelidae) Zootaxa 220753ndash66

Revell L J (2012) Phytools an R package for phylogenetic comparativebiology (and other things) Methods Ecol Evol 3 217ndash223doi 101111j2041-210X201100169x

Roper T J (1990) Responses of domestic chicks to artificially coloured insectprey effects of previous experience and background colour Anim Behav 39466ndash473 doi 101016S0003-3472(05)80410-5

Roper T J and Cook S E (1989) Responses of chicks to brightly coloured insectprey Behaviour 110 276ndash293 doi 101163156853989X00510

Roper T J and Redston S (1987) Conspicuousness of distasteful prey affectsthe strength and durability of one-trial avoidance learning Anim Behav 35739ndash747 doi 101016S0003-3472(87)80110-0

Roper T J and Wistow R (1986) Aposematic colouration and avoidancelearning in chicks Q J Exp Psychol B 38 141ndash149

Ross M S Flanagan L B and Roi G H L (1986) Seasonal and successionalchanges in light quality and quantity in the understory of boreal forestecosystems Can J Bot 64 2792ndash2799 doi 101139b86-373

Rowland H M Ihalainen E Lindstrom L Mappes J and Speed M P (2007)Co-mimics have a mutualistic relationship despite unequal defences Nature448 64ndash67 doi 101038nature05899

Ruxton G D Sherratt T N and Speed M P (2004) Avoiding Attack the

Evolutionary Ecology of Crypsis Warning Signals and Mimicry Oxford OxfordUniversity Press

Rychlik L (1999) Changes in prey size preferences during successive stages offoraging in the Mediterranean water shrew Neomys anomalus Behaviour 136345ndash365 doi 101163156853999501360

Sandre S-L Stevens M and Mappes J (2010) The effect of predator appetiteprey warning coloration and luminance on predator foraging decisionsBehaviour 147 1121ndash1143 doi 101163000579510X507001

Sandre S-L Tammaru T and Maumlnd T (2007) Size-dependent colourationin larvae of Orgyia antiqua (Lepidoptera Lymantriidae) a trade-offbetween warning effect and detectability Eur J Entomol 104 745ndash752doi 1014411eje2007095

Schulz S Gross J and Hilker M (1997) Origin of the defensive secretionof the leaf beetle Chrysomela lapponica Tetrahedron 53 9203ndash9212doi 101016S0040-4020(97)00618-2

Selman B J (1985a) The evolutionary biology and taxonomy of the AustralianEucalyptus beetles Entomography 3 451ndash454

Selman B J (1985b) The use and significance of color in the separation ofparopsine chrysomelid species Entomography 3 477ndash479

Selman B J (1994) ldquoThe biology of the paropsine eucalyptus beetles of Australiardquoin Novel Aspects of the Biology of Chrysomelidae eds P Jolivet M L Cox andE Petitpierre (Dordrecht Kluwer Academic Publishers) 555ndash565

Sharkey C R Fujimoto M S Lord N P Shin S McKenna D DSuvorov A et al (2017) Overcoming the loss of blue sensitivity throughopsin duplication in the largest animal group beetles Sci Rep 7 8doi 101038s41598-017-00061-7

Shurcliff K S (1980) Vegetation and bird community characteristics in anAustralian arid mountain range J Arid Environ 3 331ndash348

Skelhorn J Halpin C G and Rowe C (2016) Learning about aposematic preyBehav Ecol 27 955ndash964 doi 101093behecoarw009

Smith K E Halpin C G and Rowe C (2016) The benefits of being toxicto deter predators depends on prey body size Behav Ecol 27 1650ndash1655doi 101093behecoarw086

Stephens DW and Krebs J R (1986) Foraging Theory Princeton NJ PrincetonUniversity Press

Stevens M (2007) Predator perception and the interrelation betweendifferent forms of protective coloration Proc Biol Sci 274 1457ndash1464doi 101098rspb20070220

Stevens M (2013) Sensory Ecology Behaviour and Evolution Oxford OxfordUniversity Press

Stevens M Cuthill I C Windsor A M M and Walker H J (2006)Disruptive contrast in animal camouflage Proc Biol Sci 273 2433ndash2438doi 101098rspb20063614

Stevens M Parraga C A Cuthill I C Partridge J C and Troscianko T S(2007) Using digital photography to study animal coloration Biol J Linn Soc90 211ndash237 doi 101111j1095-8312200700725x

Summers K and Clough M E (2001) The evolution of coloration and toxicityin the poison frog family (Dendrobatidae) Proc Natl Acad Sci USA 986227ndash6232 doi 101073pnas101134898

Svaacutedovaacute K H Exnerovaacute A Kopeckovaacute M and Štys P (2010) Predatordependent mimetic complexes do passerine birds avoid CentralEuropean red-and-black Heteroptera Eur J Entomol 107 349ndash355doi 1014411eje2010044

Symonds M R E and Moussalli A (2011) A brief guide to modelselection multimodel inference and model averaging in behavioural ecologyusing Akaikersquos information criterion Behav Ecol Sociobiol 65 13ndash21doi 101007s00265-010-1037-6

Tan E J Reid C A M and Elgar M A (2016) Colour patternvariation affects predation in chrysomeline larvae Anim Behav 118 3ndash10doi 101016janbehav201605019

Termonia A Pasteels J M Windsor D M and Milinkovitch M C (2002)Dual chemical sequestration a key mechanism in transitions among ecologicalspecialization Proc Biol Sci 269 1ndash6 doi 101098rspb20011859

Thomas R J Marples N M Cuthill I C Takahashi M and GibsonE A (2003) Dietary conservatism may facilitate the initial evolutionof aposematism Oikos 101 458ndash466 doi 101034j1600-0706200312061x

Tischler M Dickman C R and Wardle G M (2013) Avian functional groupresponses to rainfall across four vegetation types in the Simpson Desert centralAustralia Austral Ecol 38 809ndash819 doi 101111aec12065

Tullberg B S Merilaita S and Wiklund C (2005) Aposematism and crypsiscombined as a result of distance dependence functional versatility of thecolour pattern in the swallowtail butterfly larva Proc Biol Sci 272 1315ndash1321doi 101098rspb20053079

Utne-Palm A C (2000) Prey visibility activity size and catchabilityrsquos(evasiveness) influence on Gobiusculus flavescens prey choice Sarsia 85157ndash165 doi 10108000364827200010414565

Uy F M K Ravichandran S Patel K S Aresty J Aresty P P Audett RM et al (2017) Active background choice facilitates crypsis in a tropical crabBiotropica 49 365ndash371 doi 101111btp12429

Wee J L Q and Monteiro A (2017) Yellow and the novel aposematicsignal red protect delias butterflies from predators PLoS ONE 12e0168243doi 101371journalpone0168243

Wilts B D Michielsen K Kuipers J De Raedt H and Stavenga DG (2012) Brilliant camouflage photonic crystals in the diamond weevilEntimus imperialis Proc Biol Sci 279 2524ndash2530 doi 101098rspb20112651

Woinarski J C Z and Cullen J M (1984) Distribution of invertebrateson foliage in forests of south-eastern Australia Aust J Ecol 9 207ndash232doi 101111j1442-99931984tb01359x

Zurek D B Cronin T W Taylor L A Byrne K Sullivan M L Gand Morehouse N I (2015) Spectral filtering enables trichromaticvision in colorful jumping spiders Curr Biol 25 R403ndashR404doi 101016jcub201503033

Zylinski S How M J Osorio D Hanlon R T and Marshall N J (2011) Tobe seen or to hide visual characteristics of body patterns for camouflage andcommunication in the Australian giant cuttlefish Sepia apama Am Nat 177681ndash690 doi 101086659626

Conflict of Interest Statement The authors declare that the research wasconducted in the absence of any commercial or financial relationships that couldbe construed as a potential conflict of interest

Copyright copy 2017 Tan Reid Symonds Jurado-Rivera and Elgar This is an open-

access article distributed under the terms of the Creative Commons Attribution

License (CC BY) The use distribution or reproduction in other forums is permitted

provided the original author(s) or licensor are credited and that the original

publication in this journal is cited in accordance with accepted academic practice

No use distribution or reproduction is permitted which does not comply with these

coversheet

symonds-roleoflife-2017